Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
The Penn Chinese TreeBank: Phrase structure annotation of a large corpus
Natural Language Engineering
Fertilization of case frame dictionary for robust Japanese case analysis
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Immediate-head parsing for language models
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Reliable measures for aligning Japanese-English news articles and sentences
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Fully parsing the Penn Treebank
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Analysis and repair of name tagger errors
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Being lazy and preemptive at learning toward information extraction
Being lazy and preemptive at learning toward information extraction
Labeling chinese predicates with semantic roles
Computational Linguistics
The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Merging PropBank, NomBank, TimeBank, Penn Discourse Treebank and Coreference
CorpusAnno '05 Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
The shared corpora working group report
LAW '07 Proceedings of the Linguistic Annotation Workshop
Who, what, when, where, why?: comparing multiple approaches to the cross-lingual 5W task
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Transducing logical relations from automatic and manual GLARF
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
Filtered ranking for bootstrapping in event extraction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Improving MT word alignment using aligned multi-stage parses
SSST-5 Proceedings of the Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
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We present GLARF, a framework for representing three linguistic levels and systems for generating this representation. We focus on a logical level, like LFG's F-structure, but compatible with Penn Treebanks. While less finegrained than typical semantic role labeling approaches, our logical structure has several advantages: (1) it includes all words in all sentences, regardless of part of speech or semantic domain; and (2) it is easier to produce accurately. Our systems achieve 90% for English/Japanese News and 74.5% for Chinese News -- these F-scores are nearly the same as those achieved for treebank-based parsing.